Lecturer |
Prof. Dr. Philipp Baumann |
Content |
- Students form groups and implement a machine learning system for a real-world business case
- Each group submits a written report that describes the applied algorithms and the obtained results
|
Prerequisites |
- Recommended master courses: Big Data Analytics or Portfolio Optimization
- Recommended bachelor course: Business Analytics
- Basic Python skills from recommended courses above
- Free online course that covers required Python skills: http://www.coursera.org/learn/python-data-analysis
|
Dates (preliminary) |
- 18.09.2023: Introduction and assignment of machine learning algorithms to groups
- 02.10.2023: Machine learning with Python
- 23.10.2023: Interim code review
- 03.11.2023: Submission deadline for implementation
- 06.11.2023: Presentation of guidelines for written report
- 10.11.2023: Discussion of implementation with lecturer
- 04.12.2023: Submission deadline for written report
|
Registration |
Please register until September 12 via e-mail to philipp.baumann@unibe.ch; please include an up-to-date sheet of grades. |
Further information |
KSL
ILIAS
Detailed information (as of August 16, 2023) |
Evaluation results |
Fall semester 2023 |